WO2017169284A1

WO2017169284A1 - Image processing device and method for operating same, and endoscope processor device and method for operating same

Info

Publication number: WO2017169284A1
Application number: PCT/JP2017/006198
Authority: WO
Inventors: 駿平加門
Original assignee: 富士フイルム株式会社
Priority date: 2016-04-01
Filing date: 2017-02-20
Publication date: 2017-10-05
Also published as: US20190021579A1; EP3437541A1; JP2017184861A; EP3437541A4; US10986980B2; JP6779025B2

Abstract

Provided are an image processing device and a method for operating same, as well as an endoscope processor device and a method for operating same, with which the blood vessel depth of blood vessels in an observation subject is accurately measured. A data set storage unit 97 stores a data set composed of a plurality of items of measurement data associating blood vessel indicator values such as vascular contrast and a plurality of blood vessel indicator value change factors including the blood vessel depth. A specific blood vessel indicator value change factor other than the blood vessel depth is measured. The data set is narrowed to a sub-data set having the specific blood vessel indicator value change factor. A blood vessel depth corresponding to a blood vessel indicator value calculated at a blood vessel indicator value calculation unit (vascular contrast calculation unit 96) is established from the sub-data set.

Description

Image processing apparatus and operating method thereof, endoscope processor apparatus and operating method thereof

The present invention relates to an image processing apparatus that measures the depth of a blood vessel in an observation target, an operation method thereof, an endoscope processor device, and an operation method thereof.

In the medical field, diagnosis is generally performed using an endoscope system including a light source device, an endoscope, and a processor device. In recent years, not only normal observation using broadband light such as white light but also special observation using biological function information such as oxygen saturation and blood vessel depth has been performed.

For example, in Patent Document 1, based on image signals S1, S2, and S3 obtained by sequentially irradiating narrow-band lights having center wavelengths of 445 nm, 473 nm, and 405 nm, respectively, an index value (blood vessel index value) related to blood vessels is obtained. One luminance ratio S1 / S3 and S2 / S3 is calculated, and from these luminance ratios S1 / S3 and S2 / S3, oxygen saturation and blood vessel depth are calculated, and image processing is performed by color processing such as pseudo color. Is going.

JP 2013-202189 A (Patent No. 5774531)

Regarding oxygen saturation, not only the blood vessel index values such as the luminance ratios S1 / S3 and bS2 / S3 shown in Patent Document 1, but also other measurement techniques are incorporated so that the oxygen saturation can be accurately measured. It has become. On the other hand, most of the methods for calculating the blood vessel depth using only the blood vessel index value are not possible, and the blood vessel depth may not be measured accurately for the following reasons.

For example, as shown in FIGS. 25 and 26, the relationship between the blood vessel contrast, which is one of the blood vessel index values, and the blood vessel depth is such that the blood vessel contrast increases as the blood vessel depth increases regardless of the blood vessel depth or the oxygen saturation level. There is a known tendency to be low. However, as shown in FIG. 25, the relationship between the blood vessel contrast and the blood vessel depth is different between the case where the blood vessel thickness is large and the case where the blood vessel thickness is small. It cannot be determined accurately. In addition, as shown in FIG. 26, the relationship between the blood vessel contrast and the blood vessel depth is different between when the oxygen saturation is low and when the oxygen saturation is high. It cannot be determined accurately. Therefore, there is a need for a technique that can accurately measure the blood vessel depth of the blood vessel in the observation target using not only the blood vessel index values such as the luminance ratio and the blood vessel contrast but also other information and measurement techniques.

The present invention relates to an image processing apparatus that accurately measures the blood vessel depth of a blood vessel in an observation target using not only the blood vessel index value but also other information and the like, an operating method thereof, and an endoscopic processor apparatus and its It aims to provide a method of operation.

An image processing apparatus of the present invention is an image processing apparatus that measures a blood vessel depth of a blood vessel in an observation target, an image acquisition unit that acquires an image obtained by imaging the observation target, and a blood vessel index value in the image A blood vessel index value calculating unit that calculates a blood vessel index value from the image for use, a blood vessel index value, a plurality of blood vessel index value fluctuation factors that fluctuate the blood vessel index value, and a plurality of blood vessel index value fluctuation factors including a blood vessel depth And a blood vessel index for measuring a specific blood vessel index value variation factor other than the blood vessel depth among the plurality of blood vessel index value variation factors The value variation factor measurement unit and the sub-data set having a specific vascular index value variation factor are narrowed down from the data set, and the blood vessel index value calculated by the vascular index value calculation unit is selected from the sub-data set. And a blood vessel depth calculating unit that calculates the blood vessel depth of.

It is preferable to have a measurement target blood vessel designating unit that designates a measurement target blood vessel that is a measurement target of the blood vessel depth in the observation target, and the blood vessel index value calculation unit calculates the blood vessel index value of the measurement target blood vessel. It is preferable that the blood vessel index value image includes an image of a plurality of wavelengths, and the blood vessel index value calculation unit calculates a blood vessel index value of the blood vessel to be measured based on the image of the plurality of wavelengths. The blood vessel index value calculating unit calculates a blood vessel index value for each of the images of a plurality of wavelengths, and calculates the blood vessel index value of the blood vessel to be measured by adding each weighted value to the calculated blood vessel index value, The weighting coefficient for the blood vessel index value is preferably set based on the wavelength component of the image used for calculating the blood vessel index value. It is preferable to have a blood vessel index value variation factor selection unit that selects a specific blood vessel index value variation factor measured by the blood vessel index value variation factor measurement unit from among a plurality of blood vessel index value variation factors.

It is preferable to have a blood vessel depth measurement image generation unit that generates a blood vessel depth measurement image for displaying the calculation result of the blood vessel depth calculation unit on the display unit. The blood vessel index value is preferably a value obtained by combining at least one or more of blood vessel contrast, luminance value of the blood vessel portion, and color information of the blood vessel portion. The blood vessel index value variation factor is preferably a value obtained by combining one or more of blood vessel thickness, oxygen saturation, blood vessel density, imaging distance, imaging angle, yellow pigment concentration, and mucosal scattering coefficient.

The specific blood vessel index value fluctuation factors are blood vessel thickness and oxygen saturation, and the blood vessel index value fluctuation factor measurement unit includes a blood vessel thickness measurement unit that measures blood vessel thickness and an oxygen saturation measurement that measures oxygen saturation. It is preferable to have a part. The blood vessel index value is blood vessel contrast, and the data set storage unit preferably stores a data set including measurement data in which blood vessel contrast, oxygen saturation, blood vessel depth, and blood vessel depth are associated with each other. .

The present invention relates to an endoscopic processor device for measuring a blood vessel depth of a blood vessel in an observation target, an image acquisition unit for acquiring an image obtained by imaging the observation target, and a blood vessel index value for the image A blood vessel index value calculation unit that calculates a blood vessel index value from an image, a blood vessel index value, and a plurality of blood vessel index value fluctuation factors that fluctuate the blood vessel index value and include a plurality of blood vessel index value fluctuation factors including a blood vessel depth A data set storage unit that stores a data set composed of a plurality of associated measurement data, and a blood vessel index value that measures a specific blood vessel index value variation factor other than the blood vessel depth among the plurality of blood vessel index value variation factors Fluctuation factor measurement part and sub-data set with specific vascular index value fluctuation factor in the data set are narrowed down, and it corresponds to the vascular index value calculated by the vascular index value calculation part from the sub-data set. And a blood vessel depth calculating unit that calculates the blood vessel depth.

The present invention relates to an operation method of an image processing apparatus for measuring a blood vessel depth of a blood vessel in an observation target, wherein the image acquisition unit acquires an image obtained by imaging the observation target, and calculates a blood vessel index value The blood vessel index value variation factor measurement unit is configured to calculate a blood vessel index value from the image, and the blood vessel index value variation factor measurement unit includes a plurality of blood vessel index value variation factors including a blood vessel depth. Among the factors, a step of measuring a specific blood vessel index value variation factor other than the blood vessel depth, and a plurality of measurement data in which the blood vessel depth calculation unit associates the blood vessel index value with a plurality of blood vessel index value variation factors From the data set composed of the sub-data set having a specific blood vessel index value variation factor, and the blood vessel depth corresponding to the blood vessel index value calculated by the blood vessel index value calculation unit from the sub data set And a step of obtaining.

The present invention relates to an operating method of an endoscopic processor device for measuring a blood vessel depth of a blood vessel in an observation target, wherein the image acquisition unit acquires an image obtained by imaging the observation target; The index value calculation unit calculates a blood vessel index value from a blood vessel index value image in the image, and the blood vessel index value variation factor measurement unit includes a plurality of blood vessel index value variation factors that vary the blood vessel index value. A step of measuring a specific blood vessel index value variation factor other than the blood vessel depth among a plurality of blood vessel index value variation factors including the depth, and the blood vessel depth calculation unit includes the blood vessel index value and the plurality of blood vessel index value variation factors Narrow down to a sub-data set that has a specific blood vessel index value variation factor from the data set that consists of multiple measurement data, and calculate it from the sub-data set by the blood vessel index value calculation unit And a step of obtaining a blood vessel depth corresponding to the vascular index value.

According to the present invention, by using not only the blood vessel index value but also other information, the blood vessel depth of the blood vessel in the observation target can be accurately measured.

It is an external view of an endoscope system. It is a block diagram of the endoscope system of a 1st embodiment. It is a graph which shows the spectrum of 2nd white light and blue laser beam. It is a graph which shows the spectrum of 1st white light. It is a graph which shows the spectral transmittance of a RGB color filter. It is a block diagram which shows the function of an oxygen saturation measuring part. It is a graph which shows the correlation of a signal ratio and oxygen saturation. It is a graph which shows the light absorption coefficient of oxygenated hemoglobin and reduced hemoglobin. It is explanatory drawing which shows the method of calculating oxygen saturation. It is an image figure which shows the image for blood vessel selection. It is an image figure which shows the blood vessel thickness measurement image. It is a block diagram which shows the function of the blood vessel depth measurement part. It is explanatory drawing which shows a data set. It is a graph which shows the plane on the three-dimensional space showing the relationship of the blood vessel thickness (phi), the blood vessel depth d, and the blood vessel contrast Ct in case oxygen saturation is specific value s ^* . Vessel size when oxygen saturation is a specific value s ^* phi, blood vessel depth d, a graph showing the plane of the three-dimensional space representing the relationship of the blood vessel contrast Ct, in vessel size of plane phi ^* It is a graph showing the cross section which shows a certain part. It is a graph which shows the relationship line on the two-dimensional space showing the relationship between the blood vessel depth d and the blood vessel contrast Ct in case oxygen saturation is specific value s ^* and blood vessel thickness is specific value (phi) ^* . It is an image figure which shows the blood vessel depth measurement image. It is a flowchart which shows the effect | action of an endoscope system. It is a block diagram which shows the function of the blood vessel depth measurement part to which the information input part was connected. It is a block diagram which shows the function of the blood vessel depth measurement part to which the blood vessel index value variation factor selection part was connected. It is a block diagram of the endoscope system of a 2nd embodiment. It is a graph which shows the light emission zone | band of LED (Light * Emitting * Diode), and the characteristic of HPF (High * Pass * Filter). It is a block diagram of the endoscope system of a 3rd embodiment. It is a top view of a rotation filter. It is a graph which shows the relationship between the blood vessel depth and blood vessel contrast in case blood vessel thickness differs. It is a graph which shows the relationship between the blood vessel depth and blood vessel contrast when oxygen saturation differs.

[First Embodiment]
As shown in FIG. 1, an endoscope system 10 according to the first embodiment includes an endoscope 12, a light source device 14, and a processor device 16 (an “image processing device” and an “endoscopic processor device” of the present invention). ”, A monitor 18 (corresponding to“ display unit ”of the present invention), and a console 20. The endoscope 12 is optically connected to the light source device 14 and electrically connected to the processor device 16. The endoscope 12 includes an insertion portion 21 to be inserted into a subject, an operation portion 22 provided at a proximal end portion of the insertion portion 21, a bending portion 23 and a distal end portion provided at the distal end side of the insertion portion 21. 24. By operating the angle knob 22a of the operation unit 22, the bending unit 23 performs a bending operation. With this bending operation, the distal end portion 24 can be directed in a desired direction.

In addition to the angle knob 22a, the operation unit 22 includes an observation mode switching SW 22b, a zoom operation unit 22c, and a freeze button (not shown) for storing a still image. The mode switching SW 22b is used for switching operation among four types of modes: a normal observation mode, an oxygen saturation mode, a blood vessel thickness measurement mode, and a blood vessel depth measurement mode.

The normal observation mode is a mode in which a normal light image in which the observation target in the subject is converted into a full color image is displayed on the monitor 18. The oxygen saturation mode is a mode in which an oxygen saturation image obtained by imaging the oxygen saturation of blood hemoglobin to be observed is displayed on the monitor 18. The blood vessel thickness measurement mode is a mode for measuring the thickness of the blood vessel to be observed and displaying the measurement result on the monitor 18. The blood vessel depth measurement mode is a mode in which the depth of the blood vessel to be observed is measured and the measurement result is displayed on the monitor 18. The zoom operation unit 22c is used for a zoom operation for driving the zoom lens 47 (see FIG. 2) in the endoscope 12 to enlarge the observation target.

The processor device 16 is electrically connected to the monitor 18 and the console 20. The monitor 18 displays images such as normal light images and oxygen saturation images, and information related to these images (hereinafter referred to as image information and the like). The console 20 functions as a UI (User Interface) that receives input operations such as function settings. Note that a recording unit (not shown) for recording image information or the like may be connected to the processor device 16.

As shown in FIG. 2, the light source device 14 includes a first blue laser light source (473LD (Laser Diode)) that emits a first blue laser beam having a center wavelength of 473 nm, and a second blue laser beam having a center wavelength of 445 nm. And a violet laser light source (405LD) 38 that emits violet laser light having a central wavelength of 405 nm is provided as a light emission source. The light emission amount and the light emission timing of each of the

light sources

34, 36, and 38 including these semiconductor light emitting elements are individually controlled by the light source control unit 40.

It should be noted that the half widths of the first and second blue laser beams and the violet laser beam are preferably about ± 10 nm. The center wavelengths of the first and second blue laser beams and the violet laser beam are preferably in the range of ± 5 to 10 nm with respect to the center wavelength shown above. The center wavelengths of the first and second blue laser beams and the violet laser beam may be the same as or different from the peak wavelength. The first blue laser light source 34, the second blue laser light source 36, and the violet laser light source 38 can use broad-area type InGaN laser diodes, and can also use InGaNAs laser diodes or GaNAs laser diodes. it can. The light source may be configured to use a light emitter such as a light emitting diode.

The light source control unit 40 performs control to turn on only the second blue laser light source 36 in the normal observation mode and the blood vessel thickness measurement mode. In the oxygen saturation mode and the blood vessel depth measurement mode, the light source control unit 40 performs control to alternately turn on the first blue laser light source 34 and the second blue laser light source 36 at intervals of one frame. In the normal observation mode, the oxygen saturation mode, the blood vessel thickness measurement mode, and the blood vessel depth measurement mode, when the second blue laser light source 36 is turned on, the purple laser light source 38 is also turned on simultaneously. May be performed.

The first and second blue laser light and violet laser light emitted from each of the

light sources

34, 36, and 38 are passed through optical members (all not shown) such as a condenser lens, an optical fiber, and a multiplexer. Incident on the light guide 41. The light guide 41 is built in the universal cord 17 (see FIG. 1) that connects the light source device 14 and the endoscope 12 and the endoscope 12. The light guide 41 propagates the first and second blue laser light and violet laser light from the

light sources

34, 36, and 38 to the distal end portion 24 of the endoscope 12. A multimode fiber can be used as the light guide 41. As an example, a thin fiber cable having a core diameter of 105 μm, a cladding diameter of 125 μm, and a diameter of φ0.3 to 0.5 mm including a protective layer serving as an outer shell can be used.

The distal end portion 24 of the endoscope 12 has an illumination optical system 24a and an imaging optical system 24b. The illumination optical system 24a is provided with a phosphor 44 and an illumination lens 45. The first and second blue laser light and violet laser light are incident on the phosphor 44 from the light guide 41. The phosphor 44 emits fluorescence when irradiated with the first or second blue laser light. Further, a part of the first or second blue laser light passes through the phosphor 44 as it is. On the other hand, almost all of the violet laser light passes through the phosphor 44. The light emitted from the phosphor 44 is irradiated to the observation target through the illumination lens 45.

The spectrum of light emitted to the observation target and the light emission timing are different for each mode. In the normal observation mode and the blood vessel thickness measurement mode, only the second blue laser light is incident on the phosphor 44. Therefore, as shown in FIG. 3, the second blue laser light and the second blue laser light are used to phosphor. The observation object is irradiated with second white light including green to red second fluorescence excited and emitted from 44. When the violet laser light is emitted simultaneously with the second blue laser light, the violet laser light is transmitted without being absorbed by the phosphor 44, so that the violet laser light hardly emits fluorescence.

In the oxygen saturation mode and the blood vessel depth mode, the first blue laser light and the second blue laser light are alternately incident on the phosphor 44, and as shown in FIG. First white light including green to red first fluorescence excited and emitted from the phosphor 44 by the first blue laser light and second white light are alternately irradiated on the observation target. The first fluorescence and the second fluorescence have substantially the same waveform (spectrum shape). However, in the phosphor 44, the amount of absorption with respect to the second blue laser light is larger than the amount of absorption with respect to the first blue laser light. Therefore, when the first and second blue laser beams having the same intensity enter the phosphor 44. The intensity of the entire second fluorescence wavelength is greater than the intensity of the first fluorescence.

The phosphor 44 absorbs a part of the first and second blue laser beams and excites and emits green to red light (for example, YAG phosphor or BAM (BaMgAl ₁₀ O ₁₇ )). It is preferable to use a material comprising a phosphor such as In addition, when the semiconductor light emitting element is used as an excitation light source of the phosphor 44 as in the present embodiment, high intensity first white light and second white light can be obtained with high luminous efficiency. In addition, the intensity of each white light can be easily adjusted, and changes in color temperature and chromaticity can be kept small.

The imaging optical system 24b of the endoscope 12 includes an imaging lens 46, a zoom lens 47, and a sensor 48 (see FIG. 2). Reflected light from the observation object enters the sensor 48 via the imaging lens 46 and the zoom lens 47. As a result, a reflected image of the observation object is formed on the sensor 48. The zoom lens 47 moves between the tele end and the wide end by operating the zoom operation unit 22c.

The sensor 48 is a color image sensor, picks up a reflected image of the observation object, and outputs an image signal. As the sensor 48, for example, a CCD (Charge-Coupled Device) image sensor or a CMOS (Complementary Metal-Oxide Semiconductor) image sensor can be used. In the present embodiment, the sensor 48 is a CCD image sensor. The sensor 48 has, on the imaging surface, an R pixel provided with an R color filter, a G pixel provided with a G color filter, and a B pixel provided with a B color filter. By performing photoelectric conversion on these RGB pixels, three, R, G, and B color image signals are output.

As shown in FIG. 5, the B color filter has a spectral transmittance of 380 to 560 nm, the G color filter has a spectral transmittance of 450 to 630 nm, and the spectral transmission of the R color filter 580 to 760 nm. Have a rate. Therefore, when the second white light is irradiated on the observation target in the normal observation mode and the blood vessel thickness measurement mode, the second blue laser light and a part of the green component of the second fluorescence enter the B pixel, Part of the green component of the second fluorescence is incident on the G pixel, and the red component of the second fluorescence is incident on the R pixel.

On the other hand, when the observation target is irradiated with the first white light in the oxygen saturation mode and the blood vessel depth measurement mode, the first blue laser light and a part of the green component of the first fluorescence enter the B pixel. , A part of the green component of the first fluorescence and the first blue laser light attenuated by the G color filter are incident on the G pixel, and a red component of the first fluorescence is incident on the R pixel. Since the first blue laser light has an emission intensity much higher than that of the first fluorescence, most of the B image signal output from the B pixel is occupied by the reflected light component of the first blue laser light. In the oxygen saturation mode and the blood vessel depth measurement mode, the light incident components in the RGB pixels when the second white light is irradiated onto the observation target are the same as those in the normal observation mode.

As the sensor 48, a so-called complementary color image sensor having complementary color filters of C (cyan), M (magenta), Y (yellow) and G (green) on the imaging surface may be used. When a complementary color image sensor is used as the sensor 48, the color conversion unit that performs color conversion from the CMYG four-color image signal to the RGB three-color image signal is any of the endoscope 12, the light source device 14, and the processor device 16. It should be provided in. In this way, even when a complementary color image sensor is used, it is possible to obtain RGB three-color image signals by color conversion from the four-color CMYG image signals.

The imaging control unit 49 performs imaging control of the sensor 48. In the normal observation mode and the blood vessel thickness measurement mode, the observation object illuminated with the second white light is imaged by the sensor 48 every one frame period (hereinafter simply referred to as one frame). Thus, for each frame, the sensor 48 outputs an Rc image signal from the R pixel, outputs a Gc image signal from the G pixel, and outputs a Bc image signal from the B pixel.

In the oxygen saturation mode and the blood vessel depth measurement mode, the imaging control unit 49 controls the sensor 48 to perform imaging in synchronization with the emission timings of the first white light and the second white light. Specifically, the sensor 48 reads a signal charge obtained by imaging the observation target under the first white light, outputs an R1 image signal from the R pixel, and outputs a G1 image signal from the G pixel. The B1 image signal is output from the B pixel. Then, the signal charge obtained by imaging the observation target under the second white light is read during the readout period of the second frame, the R2 image signal is output from the R pixel, and the G2 image signal is output from the G pixel. The B2 image signal is output from the B pixel.

As shown in FIG. 2, the image signal of each color output from the sensor 48 is transmitted to a CDS (correlated double sampling) / AGC (automatic gain control) circuit 50 (see FIG. 2). The CDS / AGC circuit 50 performs correlated double sampling (CDS) and automatic gain control (AGC) on the analog image signal output from the sensor 48. The image signal that has passed through the CDS / AGC circuit 50 is converted into a digital image signal by an A / D (Analog / Digital) converter 52. The digitized image signal is input to the processor device 16.

The processor device 16 includes an image signal acquisition unit 54 (corresponding to the “image acquisition unit” of the present invention), the image signal acquisition unit 54 includes a DSP (Digital Signal Processor) 56, a noise reduction unit 58, and a signal conversion unit 59. An image processing switching unit 60, a normal observation image processing unit 62, an oxygen saturation measuring unit 64 (corresponding to the “blood vessel index value variation factor measuring unit” of the present invention), an oxygen saturation image generating unit 65, A blood vessel thickness measurement unit 66, a blood vessel thickness measurement image generation unit 67, a blood vessel depth measurement unit 68 (corresponding to the “blood vessel index value variation factor measurement unit” of the present invention), and a blood vessel depth measurement image generation. Unit 69 and video signal generation unit 70.

The image signal acquisition unit 54 acquires an image signal output from the sensor 48 of the endoscope 12. The DSP 56 performs various signal processing such as defect correction processing, offset processing, gain correction processing, linear matrix processing, gamma conversion processing, demosaic processing, and YC conversion processing on the acquired image signal. In the defect correction process, the signal of the defective pixel of the sensor 48 is corrected. In the offset process, the dark current component is removed from the image signal subjected to the defect correction process, and an accurate zero level is set. The gain correction process adjusts the signal level of each image signal by multiplying each RGB image signal after the offset process by a specific gain. The image signal of each color after the gain correction processing is subjected to linear matrix processing for improving color reproducibility.

After that, the brightness and saturation of each image signal are adjusted by gamma conversion processing. The image signal after the linear matrix processing is subjected to demosaic processing (also referred to as isotropic processing or simultaneous processing), and a signal of insufficient color for each pixel is generated by interpolation. Through the demosaic processing, all pixels have signals of RGB colors. The DSP 59 performs YC conversion processing on each image signal after demosaic processing, and outputs the luminance signal Y and the color difference signals Cb, Cr generated by the YC conversion processing to the noise reduction unit 58.

The noise reduction unit 58 performs noise reduction processing by, for example, a moving average method or a median filter method on the image signal that has been demosaiced by the DSP 56. The image signal with reduced noise is input to the signal conversion unit 59, reconverted into an RGB image signal, and then input to the image processing switching unit 60.

The image processing switching unit 60 inputs the image signal that has passed through the signal conversion unit 59 to the normal observation image processing unit 62 when the normal observation mode is set. When the oxygen saturation mode is set, the image processing switching unit 60 inputs the image signal that has passed through the signal conversion unit 59 to the oxygen saturation measurement unit 64. If the blood vessel thickness measurement mode is set, the image processing switching unit 60 inputs the image signal that has passed through the signal conversion unit 59 to the blood vessel thickness measurement unit 66. When the blood vessel depth measurement mode is set, the image processing switching unit 60 inputs the image signal that has passed through the signal conversion unit 59 to the blood vessel depth measurement unit 68.

The normal observation image processing unit 62 generates RGB image data in which the input Rc image signal, Gc image signal, and Bc image signal for one frame are assigned to the R pixel, the G pixel, and the B pixel, respectively. The RGB image data is further subjected to color conversion processing such as 3 × 3 matrix processing, gradation conversion processing, and three-dimensional LUT processing. Then, various color enhancement processes are performed on the RGB image data subjected to the color conversion process. Structure enhancement processing such as spatial frequency enhancement is applied to RGB image data that has undergone color enhancement processing. The RGB image data subjected to the structure enhancement process is input to the video signal generation unit 70 as a normal observation image. The video signal generation unit 70 converts the input normal observation image into a video signal (for example, a luminance signal Y and color difference signals Cb and Cr), and outputs the converted video signal to the monitor 18. As a result, the normal observation image is displayed on the monitor 18.

The oxygen saturation measuring unit 64 is configured to calculate oxygen saturation of blood hemoglobin based on the input B1 image signal, G1 image signal, R1 image signal, B2 image signal, G2 image signal, and R2 image signal for two frames. Measure. Information on the measured oxygen saturation is sent to the oxygen saturation image generation unit 65. The oxygen saturation image generation unit 65 generates an oxygen saturation image colored according to the oxygen saturation. The generated oxygen saturation image is input to the video signal generator 70. The video signal generation unit 70 converts the input oxygen saturation image into a video signal, and outputs the converted video signal to the monitor 18. As a result, the oxygen saturation image is displayed on the monitor 18. The details of the oxygen saturation measuring unit 64 and the oxygen saturation image generating unit 65 will be described later.

The blood vessel thickness measuring unit 66 measures the blood vessel thickness of the blood vessel designated by the user based on the input Bc image signal, Gc image signal, and Rc image signal for one frame. Here, the thickness of the blood vessel (blood vessel diameter) is the distance between the boundary line of the blood vessel and the mucous membrane. For example, the number of pixels is counted from the edge of the blood vessel through the blood vessel along the short side of the blood vessel. It is the value. Therefore, the thickness of the blood vessel is the number of pixels, but if the photographing distance and zoom magnification when the image is photographed are known, it can be converted into a unit of length such as “μm” as necessary. .

The information regarding the blood vessel thickness measured by the blood vessel thickness measuring unit 66 and the Bc image signal, Gc image signal, and Rc image signal for one frame are sent to the blood vessel thickness measurement image generating unit 67. The blood vessel thickness measurement image generation unit 67 generates a blood vessel thickness measurement image in which information related to the blood vessel thickness is superimposed and displayed on the image to be observed. The generated blood vessel thickness measurement image is input to the video signal generation unit 70. The video signal generation unit 70 converts the input blood vessel thickness measurement image into a video signal and outputs the converted video signal to the monitor 18. Thereby, the blood vessel thickness measurement image is displayed on the monitor 18. Details of the blood vessel thickness measurement unit 66 and the blood vessel thickness measurement image generation unit 67 will be described later.

The blood vessel depth measuring unit 68 is a blood vessel of the blood vessel designated by the user based on the input B1 image signal, G1 image signal, R1 image signal, B2 image signal, G2 image signal, and R2 image signal for two frames. Measure depth. Information regarding the measured blood vessel depth and the B2 image signal, G2 image signal, and R2 image signal are sent to the blood vessel depth measurement image generation unit 69. The blood vessel depth measurement image generation unit 69 generates a blood vessel depth measurement image in which information related to the blood vessel depth is superimposed on the image to be observed. The generated blood vessel depth measurement image is input to the video signal generation unit 70. The video signal generation unit 70 converts the input blood vessel depth measurement image into a video signal, and outputs the converted video signal to the monitor 18. As a result, the blood vessel depth measurement image is displayed on the monitor 18. Details of the blood vessel depth measurement unit 68 and the blood vessel depth measurement image generation unit 69 will be described later.

As shown in FIG. 6, the oxygen saturation measurement unit 64 includes a signal ratio calculation unit 81, a correlation storage unit 82, and an oxygen saturation calculation unit 83. The signal ratio calculation unit 81 calculates the signal ratio B1 / G2 between the B1 image signal and the G2 image signal for each pixel, and calculates the signal ratio R2 / G2 between the R2 image signal and the G2 image signal for each pixel. When the signal ratio calculation unit 81 calculates the signal ratio B1 / G2, the signal value of the first fluorescence from the B1 image signal is calculated by inter-pixel calculation using the B1 image signal, the G1 image signal, and the R1 image signal. It is preferable to use a B1 image signal that has been subjected to correction processing for removing color and improving color separation, and corrected to a signal value substantially using only the first blue laser beam.

The correlation storage unit 82 stores the correlation between the signal ratio calculated by the signal ratio calculation unit 81 and the oxygen saturation. This correlation is stored in a two-dimensional table in which an isoline of oxygen saturation is defined on the two-dimensional space shown in FIG. The positions and shapes of the isolines with respect to the signal ratio are obtained in advance by a physical simulation of light scattering, and the interval between the isolines changes according to the blood volume (horizontal axis in FIG. 7). The correlation between this signal ratio and oxygen saturation is stored on a log scale.

The above correlation is closely related to the light absorption characteristics and light scattering characteristics of oxygenated hemoglobin (graph 90) and reduced hemoglobin (graph 91), as shown in FIG. For example, a wavelength range in which the difference between the absorption coefficients of oxyhemoglobin and reduced hemoglobin is large, such as the wavelength range near the center wavelength of 473 nm of the first blue laser beam, that is, the extinction coefficient changes depending on the oxygen saturation of blood hemoglobin. It is easy to handle oxygen saturation information in the wavelength range. However, the B1 image signal including a signal corresponding to 473 nm light is highly dependent not only on the oxygen saturation but also on the blood volume. Therefore, in addition to the B1 image signal, a signal ratio R2 / G2 obtained from a G2 image signal corresponding to light that changes mainly depending on the blood volume, and an R2 image signal serving as a reference signal for the B1 image signal and the G2 image signal. By using, oxygen saturation can be accurately obtained without depending on the blood volume.

The oxygen saturation calculation unit 83 calculates the oxygen saturation based on the image signal by using the signal ratio calculated by the signal ratio calculation unit 81. More specifically, the oxygen saturation calculation unit 83 refers to the correlation stored in the correlation storage unit 82 and calculates the oxygen saturation corresponding to the signal ratio calculated by the signal ratio calculation unit 81 for each pixel. calculate. For example, when the signal ratio B1 / G2 and the signal ratio R2 / G2 in the specific pixel are B1 ^* / G2 ^* and R2 ^* / G2 ^* , respectively, referring to the correlation as shown in FIG. 9, the signal ratio B1 ^* The oxygen saturation corresponding to / G2 ^* and the signal ratio R2 ^* / G2 ^* is “60%”. Therefore, the oxygen saturation calculation unit 83 calculates the oxygen saturation of this specific pixel as “60%”.

It should be noted that the signal ratio B1 / G2 and the signal ratio R2 / G2 are hardly increased or extremely decreased. That is, the values of the signal ratio B1 / G2 and the signal ratio R2 / G2 rarely exceed the lower limit line 93 with an oxygen saturation of 0%, and on the contrary, fall below the upper limit line 94 with an oxygen saturation of 100%. However, when the calculated oxygen saturation falls below the lower limit line 93, the oxygen saturation calculation unit 83 sets the oxygen saturation to 0%. When the calculated oxygen saturation exceeds the upper limit line 94, the oxygen saturation is set to 100. %. Further, when the points corresponding to the signal ratio B1 / G2 and the signal ratio R2 / G2 deviate from between the lower limit line 93 and the upper limit line 94, it is understood that the reliability of oxygen saturation in the pixel is low. It is also possible not to display or calculate the oxygen saturation.

The oxygen saturation image generation unit 65 uses the oxygen saturation calculated by the oxygen saturation calculation unit 83 to generate an oxygen saturation image in which the oxygen saturation is colored. Specifically, first, the oxygen saturation image generation unit 65 generates a base image based on the R2 image signal, the G2 image signal, and the B2 image signal by the same generation method as that for the normal observation image. Then, a coloring process is performed on the base image to change the color of the base image according to the oxygen saturation. Thereby, an oxygen saturation image is obtained. In the coloring process, for example, the color of the base image is not changed for a pixel region in which the oxygen saturation exceeds a specific threshold (for example, 70%), and the oxygen saturation is applied to a pixel region in which the oxygen saturation is lower than the specific threshold. It is preferable to change the color of the base image according to the degree.

Further, the oxygen saturation image may be generated using a method different from the above. For example, when an oxygen saturation image is generated using the luminance signal Y and the color difference signals Cr and Cb, the signal level of the luminance signal Y is changed according to the G2 image signal, and the color difference signals Cr and Cb are changed. It is preferable to change the signal level according to the oxygen saturation. For example, when the oxygen saturation is high, the Cr signal level is set to “positive” and the Cb signal level is set to “negative”. On the other hand, when the oxygen saturation is low, the Cr signal level is set to “negative”. It is preferable that the signal level is set to be “positive”. In this case, in the oxygen saturation image, the high oxygen region is displayed reddish while the low oxygen region is displayed bluish.

The blood vessel thickness measurement unit 66 measures the blood vessel thickness of a specific blood vessel based on the Rc image signal, the Gc image signal, and the Bc image signal. The blood vessel thickness measurement unit 66 transmits an Rc image signal, a Gc image signal, and a Bc image signal to the measurement target blood vessel specifying unit 100 in order to specify a measurement target blood vessel that is a measurement target of the blood vessel thickness (FIG. 2). reference). The measurement target blood vessel designating unit 100 generates a blood vessel selection image 102 for selecting a measurement target blood vessel based on the Rc image signal, the Gc image signal, and the Bc image signal, as shown in FIG. To display. The blood vessel selection image 102 is preferably an image obtained by extracting blood vessels by binarization processing or the like for distinguishing blood vessels from other portions. The user operates the selection pointer 104 on the blood vessel selection image 102 with an operation member such as the console 20 and designates the measurement target blood vessel TB with the selection pointer 104. The measurement target blood vessel designating unit 100 transmits information related to the measurement target blood vessel TB designated by the operation member such as the console 20 to the blood vessel thickness measurement unit 66.

When the measurement target blood vessel is designated, the blood vessel thickness measurement unit 66 specifies a pixel in a portion where the measurement target blood vessel exists among the Rc image signal, the Gc image signal, and the Bc image signal. From this specified pixel, the blood vessel thickness of the blood vessel to be measured is calculated. Specifically, the number of specified pixels (for example, in the case of FIG. 10, the number of pixels is “5 pixels”) is multiplied by the average size per pixel. Thus, the blood vessel thickness of the blood vessel to be measured is calculated. Note that since the blood vessel thickness is affected by the observation distance between the observation target and the distal end portion 24 of the endoscope, the size per pixel is preferably determined according to the observation distance.

The blood vessel thickness measurement image generation unit 67 generates a base image based on the Rc image signal, the Gc image signal, and the Bc image signal by the same generation method as that for the normal observation image. Then, the blood vessel thickness measurement image generation unit 67 performs a process of highlighting the measurement target blood vessel and superimposing and displaying the blood vessel thickness of the measurement target blood vessel on the base image. As a result, as shown in FIG. 11, a blood vessel thickness measurement image 110 displaying the highlighted measurement target blood vessel TB and the blood vessel thickness φx of the measurement target blood vessel TB is obtained.

As shown in FIG. 12, the blood vessel depth measurement unit 68 includes a blood vessel contrast calculation unit 96 (corresponding to the “blood vessel index value calculation unit” of the present invention), a data set storage unit 97, and a blood vessel depth calculation unit 98. And. In the blood vessel depth calculation unit 98, similarly to the blood vessel thickness measurement unit 66, the measurement target blood vessel to be a blood vessel depth measurement target is designated. The measurement target blood vessel is designated by the measurement target blood vessel designation unit 100 as described above. Note that the measurement target blood vessel designating unit 100 preferably generates a blood vessel selection image based on the B2 image signal, the G2 image signal, and the R2 image signal.

The blood vessel contrast calculation unit 96, based on the blood vessel contrast image signal (corresponding to the “blood vessel index value image” of the present invention) of the input image signals, the blood vessel portion pixel value Ib, and other than blood vessels such as mucous membranes Is calculated (for example, an average value of mucous membrane pixel values). The blood vessel contrast calculation unit 96 uses a blood vessel contrast image signal including an image signal with a plurality of wavelengths (corresponding to the “image with a plurality of wavelengths” of the present invention). The image signals of a plurality of wavelengths are composed of a plurality of image signals each having a different wavelength component, and in the present embodiment, correspond to the R2 image signal, the G2 image signal, and the B2 image signal. Then, the blood vessel contrast calculation unit 96 calculates the blood vessel contrast Ct by the following formula.
Formula) Ct = −Log (Ib / Im)
In the following, the blood vessel contrast Ct of the blood vessel to be measured is “Ct ^* ”.

As shown in FIG. 13, the data set storage unit 97 includes measurement data in which the blood vessel contrast Ct is associated with the oxygen saturation, the blood vessel thickness, and the blood vessel depth when the blood vessel contrast Ct is obtained. Data set 120 is stored. In the case of FIG. 13, the measurement data is stored separately for each level of oxygen saturation. Specifically, for the measurement data when the oxygen saturation is 100%, the smallest blood vessel thickness φ1 within the blood vessel thickness measurable range and the shallowest blood vessel depth d1 within the blood vessel depth measurable range. And the measurement data in which the blood vessel thickness φ1 and the blood vessel contrast Ct (100, φ1, d1) obtained in the case of the blood vessel depth d1 are associated with each other.

Similarly, all combinations of the blood vessel depths P2 to Pn with respect to the minimum blood vessel thickness φ1 and blood vessel contrasts Ct (100, φ1, d2) to Ct (100, φ1, dn) obtained when they are combined. Is also stored. In addition, for the blood vessel thicknesses φ2 to φm when the oxygen saturation is 100%, the measurement data in which the same association as described above is performed is stored. Further, even when the oxygen saturation is 0% to 99%, the measurement data in which the same association as described above is performed is stored.

The relationship between the blood vessel contrast Ct, the oxygen saturation s, the blood vessel thickness φ, and the blood vessel depth d can be expressed by the function Ct = f (s, φ, d). For this function Ct = f (s, φ, d), when the oxygen saturation s is fixed to a specific value, the blood vessel depth d is the X axis, the blood vessel thickness φ is the Y axis, and the blood vessel contrast Ct is Z On a three-dimensional space as an axis, it is represented by a plane 130 as shown in FIG. In FIG. 14, it can be seen that the blood vessel contrast decreases as the blood vessel depth increases and the blood vessel thickness decreases. On the other hand, it can be seen that the blood vessel contrast increases as the blood vessel depth decreases and the blood vessel thickness increases.

The blood vessel depth calculation unit 98 uses the blood vessel contrast Ct ^* calculated by the blood vessel contrast calculation unit 96 and the B1 image signal, B2 image signal, G2 image signal, and R2 image signal for two frames, and a data set storage unit 97. The blood vessel depth of a specific blood vessel is calculated with reference to the data set stored in (1).

The blood vessel depth calculating unit 98 sends the B1 image signal, the G2 image signal, and the R2 image signal to the oxygen saturation measuring unit 64, and the oxygen saturation measuring unit 64 measures the oxygen saturation s ^* of the blood vessel to be measured. To do. Information on the measured oxygen saturation s ^* of the blood vessel to be measured is returned to the blood vessel depth calculation unit 98. In addition, the blood vessel depth calculation unit 98 sends the B2 image signal, the G2 image signal, and the R2 image signal to the blood vessel thickness measurement unit 66, and the blood vessel thickness measurement unit 66 uses the blood vessel thickness φ ^* of the measurement target blood vessel ^. Measure.

When the oxygen saturation s ^* and the blood vessel thickness φ ^{* of the} measurement target blood vessel are obtained, the blood vessel depth calculation unit 98 selects the oxygen saturation s of the measurement target blood vessel from the data set stored in the data set storage unit 97. ^The measurement data corresponding to ^* and blood vessel thickness φ ^* is narrowed down as the first sub data set. For example, when the oxygen saturation s ^* of the measurement target blood vessel is 100% and the blood vessel thickness φ ^* is φ1, measurement of a portion corresponding to the oxygen saturation 100% and blood vessel thickness φ1 from the data set is performed. The data for use is selected as the first sub-data set (see FIG. 13).

When the first sub data set is narrowed down, the blood vessel depth calculation unit 98 calculates the blood vessel depth corresponding to the blood vessel contrast Ct ^* calculated by the blood vessel contrast calculation unit 96 with reference to the first sub data set. To do. This calculated blood vessel depth becomes the blood vessel depth of the blood vessel to be measured. For example, when the first sub data set shown in FIG. 13 is narrowed down, the blood vessel depth corresponding to the blood vessel contrast Ct ^* is “d ^* ” in the first sub data set. As described above, not only the blood vessel contrast but also the oxygen saturation measured by the oxygen saturation measuring unit 64 and the blood vessel thickness measured by the blood vessel thickness measuring unit 66, the blood vessel contrast, the oxygen saturation, the blood vessel thickness, Since the blood vessel depth of the blood vessel to be measured is calculated using the measurement data in which the blood vessel depth is associated with the blood vessel depth, the calculation accuracy of the calculated blood vessel depth was calculated using only the blood vessel contrast. It is higher than the case.

It should be noted that the relationship between the blood vessel contrast Ct, the oxygen saturation s, the blood vessel thickness φ, and the blood vessel depth d is represented by the above-described three-variable function Ct = f (s, φ, d). The calculation method is as follows. First, when the oxygen saturation s ^{* of the} blood vessel to be measured is determined, the function Ct = f (s ^* , φ, d) becomes a two-variable function with respect to the blood vessel thickness φ and the blood vessel depth d. When this two-variable function is represented in the above-described three-dimensional space, it is represented by a plane 130 shown in FIG. Further, when the blood vessel thickness φ ^* is determined, the function Ct = f (s ^* , φ ^* , d) becomes a one-variable function with respect to the blood vessel depth d.

As shown in FIG. 15, this one-variable function is equal to a cross section 132 when the blood vessel thickness φ ^* is cut along the X-axis direction on the plane 130 representing the two-variable function. Further, when the above-described one-variable function Ct = f (s ^* , φ ^* , d) is represented on a two-dimensional plane in which the X axis is the blood vessel depth d and the Y axis is the blood vessel contrast Ct, it is shown in FIG. Thus, the blood vessel contrast Ct is expressed by a function that decreases as the blood vessel depth d increases. As described above, it is possible to calculate the blood vessel depth d ^* from the blood vessel contrast Ct ^* by dropping to the one-variable function Ct = f (s ^* , φ ^* , d).

The blood vessel depth measurement image generation unit 69 generates a base image by the same generation method as that of the normal observation image based on the R2 image signal, the G2 image signal, and the B2 image signal. Then, the blood vessel depth measurement image generation unit 69 performs a process of highlighting the measurement target blood vessel and superimposing and displaying the blood vessel depth of the measurement target blood vessel on the base image. As a result, as shown in FIG. 17, a blood vessel depth measurement image 150 displaying the highlighted measurement target blood vessel TB and the blood vessel depth d ^* of the measurement target blood vessel TB is obtained.

Next, the flow of observation by the endoscope system 10 of the present embodiment will be described along the flowchart of FIG. First, in the normal observation mode, the user observes an observation target and detects a site that may be a lesion. And when the site | part which may be a lesioned part is discovered, in order to measure the blood vessel depth about the blood vessel of the part, mode switch SW22b is operated and it switches to the blood vessel depth measurement mode.

When switched to the blood vessel depth measurement mode, the first and second white lights are alternately irradiated onto the observation target in synchronization with the imaging frame of the sensor 48. The sensor 48 outputs an R1 image signal, a G1 image signal, and a B1 image signal in the first frame, and outputs an R2 image signal, a G2 image signal, and a B2 image signal in the second frame. These image signals are acquired by the image signal acquisition unit 54 of the processor device 16 and subjected to various signal processing.

Then, a blood vessel selection image 102 is generated based on the R2 image signal, the G2 image signal, and the B2 image signal, and displayed on the monitor 18. The user selects a portion of a blood vessel that may be a lesion in the blood vessel selection image 102 as a measurement target blood vessel. When the measurement target blood vessel is selected, the blood vessel contrast calculation unit 96 calculates the blood vessel contrast Ct ^* of the measurement target blood vessel. Also, the B1 image signal, the G2 image signal, and the R2 image signal are sent to the oxygen saturation measuring unit 64, and the oxygen saturation measuring unit 64 measures the oxygen saturation s ^{* of the} blood vessel to be measured. In addition, the R2 image signal, the G2 image signal, and the B2 image signal are sent to the blood vessel thickness measuring unit 66, and the blood vessel thickness measuring unit 66 measures the blood vessel thickness φ ^* of the measurement target blood vessel.

After measuring the oxygen saturation s ^* and the blood vessel thickness φ ^* of the measurement target blood vessel, the blood vessel depth calculation unit 98 selects the oxygen saturation of the measurement target blood vessel from the data set stored in the data set storage unit 97. The measurement data corresponding to s ^* and blood vessel thickness φ ^* is narrowed down as the first sub data set. When the first sub data set is narrowed down, the blood vessel depth calculation unit 98 refers to the first sub data set and determines the blood vessel depth corresponding to the blood vessel contrast Ct ^* of the measurement target blood vessel. Calculated as depth d ^* . After the blood vessel depth d ^* of the measurement target blood vessel is calculated, a blood vessel depth measurement image is generated based on the information on the blood vessel depth d ^* of the measurement target blood vessel and the R2 image signal, the G2 image signal, and the B2 image signal. And displayed on the monitor 18.

In the above embodiment, the blood vessel contrast calculation unit 96 weights the R2 image signal, the G2 image signal, and the B2 image signal, and based on the weighted R2 image signal, G2 image signal, and B2 image signal. Thus, the blood vessel contrast of the blood vessel to be measured may be calculated. For example, in the blood vessel selection image 102, the approximate blood vessel depth (measured blood vessel depth) of the blood vessel to be measured is visually measured by the user, and weighting is performed according to the measured blood vessel depth. The weighting is set by an operation member such as the console 20.

Here, when the target blood vessel depth is shallow, blood vessels located in a shallow portion such as a surface blood vessel are included in a short wavelength image signal. Therefore, the B2 image signal included in the short wavelength image signal is weighted. The weighting is set larger than the other weights for the G2 image signal and the R2 image signal. On the other hand, when the target blood vessel depth is deep, a lot of blood vessels located in a deep part such as a middle-deep blood vessel are included in the long-wavelength image signal. The weight is set larger than the weights for the other B2 image signal and R2 image signal. As described above, the calculation accuracy of the blood vessel contrast of the measurement target blood vessel can be improved by increasing the weighting of the image signal in the wavelength band including the measurement target blood vessel. This improvement in blood vessel contrast calculation accuracy leads to an improvement in blood vessel depth calculation accuracy.

In addition, the blood vessel contrast calculation unit 96 calculates the blood vessel contrast for each of the R2 image signal, the G2 image signal, and the B2 image signal, and calculates the blood vessel contrast of the measurement target blood vessel by combining the calculated blood vessel contrast. May be. As a method of calculating by combining the blood vessel contrast, for example, a weighted average process for weighting and adding the blood vessel contrast can be considered. When performing this weighted average processing, it is preferable to set the weighting coefficient for each blood vessel contrast based on the wavelength component of the image signal used for calculating the blood vessel contrast.

For example, the weighting coefficient of the blood vessel contrast Ctr obtained from the R2 image signal is α, the weighting coefficient of the blood vessel contrast Ctg obtained from the G2 image signal is β, and the weighting coefficient of the blood vessel contrast Ctb obtained from the B2 image signal is γ. Then, the blood vessel contrast of the blood vessel to be measured is “α × Ctr + β × Ctg + γ × Ctb”. When the blood vessel to be measured is a surface blood vessel, it is preferable that the weighting coefficient γ is larger than the other weighting coefficients α and β. Each blood vessel contrast Ctr, Ctg, and Ctb indicates the blood vessel contrast for the same blood vessel of interest.

In the above embodiment, the oxygen saturation s ^* of the measurement target blood vessel measured by the oxygen saturation measurement unit 64 and the blood vessel thickness φ ^* of the measurement target blood vessel measured by the blood vessel thickness measurement unit 66 are used. The first sub data set having the oxygen saturation s ^* and the blood vessel thickness φ ^* of the blood vessels to be measured is narrowed down. However, the sub data sets may be narrowed down by other methods. For example, as shown in FIG. 19, the information input unit 160 connected to the blood vessel depth calculation unit 98 manually inputs the oxygen saturation s ^** and the blood vessel thickness φ ^** of the blood vessel to be measured. The blood vessel depth calculation unit 98 narrows down the measurement data having the input oxygen saturation s ^** and blood vessel thickness φ ^** of the measurement target blood vessel as the second sub data set. Also in the case of this second sub data set, the blood vessel depth is calculated in the same manner as in the first sub data set. Note that the function of the information input unit 160 may be incorporated in the console 20.

As described above, as a situation where the oxygen saturation s ^** and the blood vessel thickness φ ^** of the blood vessel to be measured are manually input, before the blood vessel depth is measured, the user already has an oxygen saturation image and A situation in which an approximate oxygen saturation and a blood vessel thickness are recognized by looking at a blood vessel thickness measurement image can be considered. The blood vessel depth calculation unit 98 uses the first sub-data based on the oxygen saturation s ^* and the blood vessel thickness φ ^* of the blood vessel to be measured measured by the oxygen saturation measurement unit 64 and the blood vessel thickness measurement unit 66. Two modes can be executed: automatic mode for narrowing the set and manual mode for narrowing the second sub-data set based on the manually input oxygen saturation s ^** and blood vessel thickness φ ^** of the blood vessel to be measured It may be in a state. In this case, the operation member such as the console 20 is selectively set to either the automatic mode or the manual mode.

In the above embodiment, the blood vessel contrast is used to calculate the blood vessel depth, but other blood vessel index values may be used. Examples of the blood vessel index value include luminance values (average value and the like) of the measurement target blood vessel and color information of the measurement target blood vessel. As color information, calculation values obtained by calculation based on R2 image signal, G2 image signal, and B2 image signal, for example, signal ratio such as R2 / G2, B2 / G2, color difference signals Cr, Cb, saturation S, Hue H and the like. The blood vessel index value may be a value obtained by combining the blood vessel contrast, the luminance value of the blood vessel portion, and the color information of the blood vessel portion.

In the above embodiment, the relationship between the blood vessel contrast, the oxygen saturation, the blood vessel thickness, and the blood vessel depth is determined, and the oxygen saturation and the blood vessel depth other than the blood vessel depth are measured. Although the blood vessel depth was calculated by using the measurement result and the relationship, the blood vessel index value such as the blood vessel contrast and the blood vessel index value fluctuation factor that fluctuates the blood vessel index value are used. The blood vessel depth is calculated by measuring the specific blood vessel index value fluctuation factor after determining the relationship between the specific blood vessel index value fluctuation factor and the blood vessel depth in advance and using the measurement result and the relationship. You may make it do.

In this case, in order to be able to select or add a specific blood vessel index value fluctuation factor from among a plurality of blood vessel index value fluctuation factors, as shown in FIG. It is preferable that a selection data set composed of associated measurement data is stored in the selection data set storage unit 165 in advance. When a specific blood vessel index value variation factor is selected by the blood vessel index value variation factor selection unit 170 connected to the blood vessel depth measurement unit 68, a selection data set corresponding to the selected blood vessel index value variation factor is selected. Are read from the selection data set storage unit 165 and integrated as one data set. The integrated data set is stored in the data set storage unit 97, and the blood vessel depth is calculated by the same method. When a specific blood vessel index value variation factor other than oxygen saturation and blood vessel thickness is selected, a specific measurement unit that can measure the specific blood vessel index value variation factor is newly required.

When there are a plurality of specific blood vessel index value fluctuation factors, a part is fixed at a representative value (for example, “70%” in the case of oxygen saturation), and other specific blood vessel index value fluctuation factors are blood vessels. A data set in which the index value and the blood vessel depth are associated with each other is preferable. In this case, measurement or input of some specific blood vessel index value fluctuation factors fixed with representative values is not performed, and measurement or input of other specific blood vessel index value fluctuation factors is performed.

The specific blood vessel index value fluctuation factors include the following in addition to the oxygen saturation and the blood vessel thickness. For example, since the imaging distance and imaging angle are specific blood vessel index value fluctuation factors that change the blood vessel contrast, the blood vessel depth is calculated from the relationship between the blood vessel contrast, the imaging distance or imaging angle, and the blood vessel depth. You may make it do. Further, since the blood vessel density is a specific blood vessel index value fluctuation factor that fluctuates the blood vessel contrast, the blood vessel depth may be calculated from the relationship between the blood vessel contrast, the blood vessel density, and the blood vessel depth. . Other specific blood vessel index value fluctuation factors include the concentration of yellow pigments such as bilirubin and the mucosal scattering coefficient. Note that the photographing distance is preferably calculated from the average luminance of the entire mucous membrane. The photographing angle is preferably estimated from the luminance distribution of the entire image. The blood vessel density is preferably calculated based on the extracted blood vessel region extracted from the image.

[Second Embodiment]
As shown in FIG. 21, the light source device 14 of the endoscope system 200 includes LED (Light Emitting Diode) instead of the first and second blue laser light sources 34 and 36, the violet laser light source 38, and the light source control unit 40. A light source unit 201 and an LED light source control unit 204 are provided. In addition, the phosphor 44 is not provided in the illumination optical system 24a of the endoscope system 200. Other than that, it is the same as the endoscope system 10 of the first embodiment.

The LED light source unit 201 includes an R-LED 201a, a G-LED 201b, a B-LED 201c, and a V-LED 201d as light sources that emit light limited to a specific wavelength band. As shown in FIG. 22, the R-LED 201a emits red band light (hereinafter simply referred to as red light) of about 600 to 650 nm, for example. The center wavelength of the red light is about 620 to 630 nm. The G-LED 201b emits about 500 to 600 nm of green band light (hereinafter simply referred to as green light) represented by a normal distribution. The B-LED 201c emits blue band light having a central wavelength of 445 to 460 nm (hereinafter simply referred to as blue light). The V-LED 201d emits purple band light having a central wavelength of 400 to 410 nm (hereinafter simply referred to as purple light).

Also, the LED light source unit 201 has a high-pass filter (HPF) 202 that is inserted into and extracted from the optical path of blue light emitted from the B-LED 201c. The high pass filter 202 cuts blue light having a wavelength band of about 450 nm or less. The blue light from which the wavelength band of about 450 nm or less is cut is composed of a wavelength band (see FIG. 8) in which the absorption coefficient of oxyhemoglobin is larger than that of reduced hemoglobin, and is used for measuring oxygen saturation. be able to. Therefore, hereinafter, blue light from which a wavelength band of about 450 nm or less is cut is referred to as measurement blue light. The high-pass filter 202 is inserted / removed by the HPF insertion / removal unit 203 under the control of the LED light source control unit 204.

The LED light source control unit 204 controls turning on / off of each LED 201a to 201d of the LED light source unit 201, each emission amount, and insertion / extraction of the high-pass filter 202. Specifically, in the normal observation mode and the blood vessel thickness measurement mode, the LED light source control unit 204 turns on all the LEDs 201a to 201d, and the high-pass filter 202 retracts the B-LED 301c from the optical path. Thereby, white light on which purple light, blue light, green light, and red light are superimposed is irradiated on the observation target, and the sensor 48 images the observation target with the reflected light, and the Bc image signal, the Gc image signal, and the Rc image. Output a signal.

On the other hand, in the oxygen saturation mode and the blood vessel depth measurement mode, the LED light source control unit 204 turns on only the B-LED 203d and all LEDs 203a to 203d with the high-pass filter 202 inserted. Control to switch alternately every frame. As a result, the observation target is alternately irradiated with measurement blue light and mixed light including violet light, measurement blue light, green light, and red light.

Then, the imaging control unit 49 reads out the signal charge obtained by imaging the observation target under the measurement blue light during the readout period of the first frame, and outputs the B1 image signal, the G1 image signal, and the R1 image signal. Output. In addition, a signal charge obtained by imaging an observation target under mixed light including purple light, measurement blue light, green light, and red light is read out during a readout period of the second frame, and a B2 image signal is obtained. A G2 image signal and an R2 image signal are output. Subsequent processing can be performed in the same manner as the endoscope system 10.

[Third Embodiment]
As shown in FIG. 23, the light source device 14 of the endoscope system 300 includes a broadband light source 301 instead of the first and second blue laser light sources 34 and 36, the violet laser light source 38, and the light source control unit 40. A filter 302 and a rotation filter control unit 303 are provided. In addition, the sensor 305 of the endoscope system 300 is a monochrome image sensor that is not provided with a color filter. For this reason, the DSP 56 does not perform processing peculiar to the color image sensor such as demosaic processing. About other than that, it is the same as the endoscope system 10 of 1st Embodiment.

The broadband light source 301 includes, for example, a xenon lamp, a white LED, and the like, and emits white light whose wavelength band ranges from blue to red. The rotary filter 302 includes a first filter 310 and a second filter 311 (see FIG. 24), and the first filter 310 is placed on the optical path where white light emitted from the broadband light source 301 enters the light guide 41. It can move in the radial direction between the first position where it is disposed and the second position where the second filter 311 is disposed.

The mutual movement of the rotary filter 302 to the first position and the second position is controlled by the rotary filter control unit 303 according to the selected observation mode. The rotation filter 302 rotates in accordance with the imaging frame of the sensor 305 in a state where the rotation filter 302 is disposed at the first position or the second position. The rotation speed of the rotation filter 302 is controlled by the rotation filter control unit 303 according to the selected observation mode.

As shown in FIG. 24, the first filter 310 is used in the normal observation mode and the blood vessel thickness measurement mode, and is provided on the inner peripheral portion of the rotary filter 302. The first filter 310 includes an R filter 310a that transmits red light, a G filter 310b that transmits green light, and a B filter 310c that transmits blue-violet light including violet light and blue light. When the normal observation mode and the blood vessel thickness measurement mode are set, the rotary filter 302 is disposed at the first position, and the white light from the broadband light source 301 is output from the R filters 310a and G according to the rotation of the rotary filter 302. The light enters one of the filter 310b and the B filter 310c. For this reason, the observation object is sequentially irradiated with red light, green light, and blue-violet light according to the transmitted filter. The sensor 305 sequentially outputs an Rc image signal, a Gc image signal, and a Bc image signal by imaging the observation target with these reflected lights.

The second filter 311 is used in the oxygen saturation mode and the blood vessel depth measurement mode, and is provided on the outer peripheral portion of the rotary filter 302. The second filter 311 includes an R filter 311a that transmits red light, a G filter 311b that transmits green light, a B filter 311c that transmits blue-violet light including violet light and blue light, and a narrow band of 473 ± 10 nm. A narrow band filter 311d that transmits light. When the oxygen saturation mode and the blood vessel depth measurement mode are set, the rotation filter 302 is disposed at the second position, and the white light from the broadband light source 301 is converted into an R filter 311a according to the rotation of the rotation filter 302. The light enters one of the G filter 311b, the B filter 311c, and the narrow band filter 311d. Therefore, the observation target is sequentially irradiated with red light, green light, blue-violet light, and narrowband light (473 nm) according to the transmitted filter.

The sensor 405 captures the observation target when the red light is irradiated and outputs an R2 image signal. When the green light is irradiated, the sensor 405 captures the observation target and outputs a G2 image signal. When the light is irradiated, the observation target is imaged and a B2 image signal is output, and when the narrow band light is irradiated, the observation target is imaged and the B1 image signal is output. Subsequent processing can be performed similarly to the endoscope system 10 of the first embodiment.

In the first to third embodiments, the oxygen saturation is calculated. Instead of or in addition to this, an oxygenated hemoglobin index obtained from “blood volume × oxygen saturation (%)” or “blood volume” Other biological function information such as a reduced hemoglobin index obtained from “× (1-oxygen saturation) (%)” may be calculated.

DESCRIPTION OF SYMBOLS 10 Endoscope system 12 Endoscope 14 Light source apparatus 16 Processor apparatus 17 Universal code 18 Monitor 20 Console 21 Insertion part 22 Operation part 22a Angle knob 22c Zoom operation part 23 Bending part 24 Tip part 24a Illumination optical system 24b Imaging optical system 34 First blue laser light source 36 Second blue laser light source 38 Purple laser light source 40 Light source control unit 41 Light guide 44 Phosphor 45 Illumination lens 46 Imaging lens 47 Zoom lens 48 Sensor 49 Imaging control unit 50 CDS / AGC circuit 52 A / D conversion 54 Image signal acquisition unit 56 DSP
58 Noise reduction unit 59 Signal conversion unit 60 Image processing switching unit 62 Normal observation image processing unit 64 Oxygen saturation measurement unit 65 Oxygen saturation image generation unit 66 Blood vessel thickness measurement unit 67 Blood vessel thickness measurement image generation unit 68 Blood vessel depth Measurement unit 69 Blood vessel depth measurement image generation unit 70 Video signal generation unit 81 Signal ratio calculation unit 82 Correlation storage unit 83 Oxygen saturation calculation unit 90 Graph 91 Graph 93 Lower limit line 94 Upper limit line 96 Blood vessel contrast calculation unit 97 Data set storage Unit 98 Blood vessel depth calculation unit 100 Measurement target blood vessel designation unit 102 Blood vessel selection image 104 Selection pointer 110 Blood vessel thickness measurement image 120 Data set 150 Blood vessel depth measurement image 160 Information input unit 170 Blood vessel index value variation factor selection unit 200 Endoscope system 201 LED light source unit 202 High pass filter 203 Insertion / extraction section 204 Light source control Control unit 300 Endoscope system 301 Broadband light source 302 Rotating filter 303 Rotating filter control unit 305 Sensor 310 First filter 310a R filter

310b G filter

310c B filter 311 Second filter 311a R filter

311b G filter

311c B filter 311d Narrow band filter 405 sensor

Claims

An image processing apparatus for measuring a blood vessel depth of a blood vessel in an observation target,
An image acquisition unit for acquiring an image obtained by imaging the observation target;
A blood vessel index value calculation unit for calculating a blood vessel index value from the image for blood vessel index value of the image;
Data composed of a plurality of measurement data in which the blood vessel index value is associated with a plurality of blood vessel index value variation factors that vary the blood vessel index value and include a blood vessel depth A data set storage unit for storing the set;
A blood vessel index value fluctuation factor measurement unit that measures a specific blood vessel index value fluctuation factor other than the blood vessel depth among the plurality of blood vessel index value fluctuation factors;
A blood vessel that narrows down the sub-data set having the specific blood vessel index value variation factor from the data set, and obtains a blood vessel depth corresponding to the blood vessel index value calculated by the blood vessel index value calculation unit from the sub data set An image processing apparatus comprising a depth calculation unit.
A measurement target blood vessel designating unit for designating a measurement target blood vessel to be a measurement target of the blood vessel depth in the observation target;
The image processing apparatus according to claim 1, wherein the blood vessel index value calculation unit calculates a blood vessel index value of the measurement target blood vessel.
The blood vessel index value image includes an image of a plurality of wavelengths,
The image processing apparatus according to claim 2, wherein the blood vessel index value calculation unit calculates a blood vessel index value of the measurement target blood vessel based on the images of the plurality of wavelengths.
The blood vessel index value calculation unit calculates a blood vessel index value for each of the images of the plurality of wavelengths, and adds the weighted index value to the calculated blood vessel index value, thereby calculating the blood vessel index value of the measurement target blood vessel. Calculate
The image processing apparatus according to claim 3, wherein the weighting coefficient for the blood vessel index value is set based on a wavelength component included in the image used for calculating the blood vessel index value.
5. The blood vessel index value variation factor selection unit that selects a specific blood vessel index value variation factor measured by the blood vessel index value variation factor measurement unit from the plurality of blood vessel index value variation factors. The image processing apparatus according to claim 1.
6. The image processing apparatus according to claim 1, further comprising a blood vessel depth measurement image generation unit that generates a blood vessel depth measurement image for displaying a calculation result of the blood vessel depth calculation unit on a display unit.
The image processing apparatus according to any one of claims 1 to 6, wherein the blood vessel index value is a value obtained by combining at least one of blood vessel contrast, luminance value of the blood vessel portion, and color information of the blood vessel portion.
The blood vessel index value variation factor is a value obtained by combining one or more of blood vessel thickness, oxygen saturation, blood vessel density, imaging distance, imaging angle, yellow pigment concentration, and mucosal scattering coefficient. 8. The image processing device according to any one of claims 7.
The specific blood vessel index value variation factors are blood vessel thickness and oxygen saturation,
The image according to any one of claims 1 to 8, wherein the blood vessel index value variation factor measurement unit includes a blood vessel thickness measurement unit that measures the blood vessel thickness and an oxygen saturation measurement unit that measures the oxygen saturation. Processing equipment.
The blood vessel index value is blood vessel contrast;
The image according to claim 9, wherein the data set storage unit stores a data set including measurement data in which the blood vessel contrast, the oxygen saturation, the blood vessel depth, and the blood vessel depth are associated with each other. Processing equipment.
An endoscope processor device for measuring a blood vessel depth of a blood vessel in an observation object,
An image acquisition unit for acquiring an image obtained by imaging the observation target;
A blood vessel index value calculation unit for calculating a blood vessel index value from the image for blood vessel index value of the image;
Data composed of a plurality of measurement data in which the blood vessel index value is associated with a plurality of blood vessel index value variation factors that vary the blood vessel index value and include a blood vessel depth A data set storage unit for storing the set;
A blood vessel index value fluctuation factor measurement unit that measures a specific blood vessel index value fluctuation factor other than the blood vessel depth among the plurality of blood vessel index value fluctuation factors;
A blood vessel that narrows down the sub-data set having the specific blood vessel index value variation factor from the data set, and obtains a blood vessel depth corresponding to the blood vessel index value calculated by the blood vessel index value calculation unit from the sub data set An endoscopic processor device comprising a depth calculation unit.
An operation method of an image processing device for measuring a blood vessel depth of a blood vessel in an observation object,
An image acquisition unit acquiring an image obtained by imaging the observation target;
A blood vessel index value calculating unit calculating a blood vessel index value from a blood vessel index value image in the image;
The blood vessel index value variation factor measurement unit is a plurality of blood vessel index value variation factors that vary the blood vessel index value, and among the plurality of blood vessel index value variation factors including the blood vessel depth, a specific blood vessel index other than the blood vessel depth Measuring the value fluctuation factor;
A blood vessel depth calculation unit has the specific blood vessel index value variation factor from a data set composed of a plurality of measurement data in which the blood vessel index value and the plurality of blood vessel index value variation factors are associated with each other. A method of operating the image processing apparatus, comprising: narrowing down to a sub-data set and obtaining a blood vessel depth corresponding to the blood vessel index value calculated by the blood vessel index value calculation unit from the sub-data set.
An operation method of a processor device for an endoscope for measuring a blood vessel depth of a blood vessel in an observation object,
An image acquisition unit acquiring an image obtained by imaging the observation target;
A blood vessel index value calculating unit calculating a blood vessel index value from a blood vessel index value image in the image;
The blood vessel index value variation factor measurement unit is a plurality of blood vessel index value variation factors that vary the blood vessel index value, and among the plurality of blood vessel index value variation factors including the blood vessel depth, a specific blood vessel index other than the blood vessel depth Measuring the value fluctuation factor;
A blood vessel depth calculation unit has the specific blood vessel index value variation factor from a data set composed of a plurality of measurement data in which the blood vessel index value and the plurality of blood vessel index value variation factors are associated with each other. And a step of narrowing down to a sub-data set and obtaining a blood vessel depth corresponding to the blood vessel index value calculated by the blood vessel index value calculating unit from the sub-data set.